Plot empirical densities kernel estimate

If more than 2 list elements or data.frame columns, NotImplemented error.

Usage

plot_density_empirical(
  df,
  xmin = NULL,
  xmax = NULL,
  n_density = 512,
  length.out = 250,
  colors_pos_neg_both = colors_pos_neg_both_default,
  positive_label = NULL,
  ...
)

Arguments

df

data.frame or list of values. The names will be the legends, the values will be used to estimate the densities.

xmin

If given, the densities are restricted/shown from this value on

xmax

If given, the densities are restricted/shown until this value

n_density

Parameter of density(), from that documentation: The number of equally spaced points at which the density is to be estimated. When n > 512, it is rounded up to a power of 2 during the calculations (as fft is used) and the final result is interpolated by approx. So it almost always makes sense to specify n as a power of two.

length.out

After calculating the density, how many values should be used to plot the density

colors_pos_neg_both

Colors for positive ("+"), negative ("-") and overlapping "+/-" areas of the densities

positive_label

If positive_label is given, set this as the "+" density.

...

Convenience, not used in this function though.

Value

ggplot of the empirical densities

Details

1. Calculates density estimates per list-element/column with [density()]
2. Approximates the estimated densities with [stats::approx()] for equally
spaced `length.out` elements between xmin and xmax
3. If `positive_label` is given, set this as the "+" density.

Examples

sim_samples <- sim(
    list(
        "dist_1" = function(x) rnorm(x, mean = 1, sd = 1),
        "dist_2" = function(x) rnorm(x, mean = 0, sd = 1)
    ),
    do_melt = FALSE
)
plot_density_empirical(sim_samples)